Quantitative Performance Comparison of Thermal Structure Function Computations

Abstract

The determination of thermal structure functions from transient thermal measurements using network identification by deconvolution is a delicate process as it is sensitive to noise in the measured data. Great care must be taken not only during the measurement process but also to ensure a stable implementation of the algorithm. In this paper, a method is presented that quantifies the absolute accuracy of network identification on the basis of different test structures. For this purpose, three measures of accuracy are defined. By these metrics, several variants of network identification are optimized and compared against each other. Performance in the presence of noise is analyzed by adding Gaussian noise to the input data. In the cases tested, the use of a Bayesian deconvolution provided the best results.